You can not select more than 25 topics Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.

74 lines
2.6 KiB

5 months ago
# -*- coding: utf-8 -*-
import cv2
import os
import numpy as np
from PIL import Image
from psd_tools import PSDImage
def file_inspect():
# 文件路径
png_file = 'K:/work/mine_clearance/class1/userfiles/result11.png'
psd_file = 'K:/work/mine_clearance/class1/userfiles/result11.psd'
result_png = 'K:/work/mine_clearance/class1/result4.png'
# 检查文件是否存在
if os.path.exists(png_file) and os.path.exists(psd_file):
if psd_to_png(psd_file, result_png):
if image_similarity(png_file, result_png) < 0.99:
print('result3.psd文件与result3.png不匹配')
return 0
return 1
return 0
else:
print('缺少文件')
return 0
def image_specifications():
# 打开图像文件
image = Image.open('K:/work/mine_clearance/class1/userfiles/result11.png')
image2 = Image.open('K:/work/mine_clearance/class1/result4.png')
# 获取图像尺寸(宽度和高度)
width, height = image2.size
width2, height2 = image.size
width_difference = abs(width - width2)
height_difference = abs(height - height2)
if width_difference > 20 or height_difference > 20:
print('图片未按照规格修改,请修改在测试!')
def similitude():
image1 = 'K:/work/mine_clearance/class1/userfiles/result11.png'
image2 = 'K:/work/mine_clearance/class1/result2.png'
similarity = image_similarity(image1, image2)
if similarity > 0.6 and similarity < 0.99:
print('海报制作成功')
elif similarity == 1:
print('请自己制作!')
else:
print('还需要进一步修改')
print("图像相似度: {:.2f}%".format(similarity*100))
def psd_to_png(psd_path, png_path):
try:
psd_image = PSDImage.open(psd_path)
image_pil = psd_image.topil()
image_np = cv2.cvtColor(np.array(image_pil), cv2.COLOR_RGB2BGR)
cv2.imwrite(png_path, image_np)
return 1
except Exception as e:
print("psd文件与png文件相同大小")
return 0
def image_similarity(image1, image2):
# 读取图片
img1 = cv2.imread(image1)
img2 = cv2.imread(image2)
# 将图片调整为相同尺寸
img1 = cv2.resize(img1, img2.shape[:2][::-1])
# 计算直方图差异
hist1 = cv2.calcHist([img1], [0, 1, 2], None, [8, 8, 8], [0, 256, 0, 256, 0, 256])
hist2 = cv2.calcHist([img2], [0, 1, 2], None, [8, 8, 8], [0, 256, 0, 256, 0, 256])
similarity = cv2.compareHist(hist1, hist2, cv2.HISTCMP_CORREL)
return similarity
if __name__=="__main__":
if file_inspect():
similitude()
image_specifications()